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首页> 外文期刊>International journal of mobile computing and multimedia communications >A Novel Fast Hierarchical Projection Algorithm for Skew Detection in Multimedia Big Data Environment
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A Novel Fast Hierarchical Projection Algorithm for Skew Detection in Multimedia Big Data Environment

机译：多媒体大数据环境中倾斜检测的快速分层投影新算法

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摘要

Optical character recognition is an effective way for information input of paper media and skew detection of document images is a key stage of it. An algorithm for skew detection employing hierarchical projection is proposed in this paper. Projection histograms at various directions in a given range are acquired according to an initial angle step length. Then variances of it and absolute difference of the variances are calculated respectively and the angle corresponding to the maximum difference is served as rough skew estimate. The similar work above is implemented in which the projection angle range is two times the initial step length and symmetric about the estimate. Finally, the maximum value of the variances is found and the angle corresponding to it is served as skew angle. Experimental results show the algorithm has such advantages as fast processing speed, high detection accuracy, insensitivity to noise and suitable for complex layout.
机译：光学字符识别是纸质介质信息输入的有效方式，而文档图像的倾斜检测是其关键阶段。提出了一种基于层次投影的偏斜检测算法。根据初始角度步长，获取给定范围内各个方向的投影直方图。然后分别计算其方差和方差的绝对差，并将与最大差相对应的角度用作粗偏估计。实施上述类似的工作，其中投影角度范围是初始步长的两倍，并且关于估计对称。最后，找到方差的最大值，并将与之对应的角度用作偏斜角。实验结果表明，该算法具有处理速度快，检测精度高，对噪声不敏感，适合复杂布局等优点。

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